Iowa State University scientists have harnessed data analytics to look “under the hood” of the mechanisms that determine how genetics and changing environmental conditions interact during crucial developmental stages of plants.
In March of 2021, a decade of hard work and persistence paid off as Katherine Frels moved back to Lincoln and into the field, not as a graduate student but as the first female small grains breeder in University of Nebraska history.
Iowa State University scientists are leading an effort to improve efficiency and genetics in organic corn production, a fast-growing sector of the agricultural world since the beginning of 2020.
Thomas Lübberstedt, a professor of agronomy at Iowa State, leads a research team aiming to develop new lines of corn that take advantage of recent advancements in crop genetics that also can be grown according to organic standards. The research team recently received a $1.4 million grant from the U.S. Department of Agriculture’s National Institute of Food and Agriculture to apply genetic tools to the development of organic sweet corn and varieties of corn for specialty uses, such as for popcorn and tortillas.
Improved, practical crop breeding tools are essential to meet the increasing global demands for sustainable food production, made more urgent by the unpredictable stresses driven by a changing climate.
Scientists have invested great time and effort into making connections between a plant’s genotype, or its genetic makeup, and its phenotype, or the plant’s observable traits. Understanding a plant’s genome helps plant biologists predict how that plant will perform in the real world, which can be useful for breeding crop varieties that will produce high yields or resist stress.
Findings from an Iowa State University research team challenge previous understanding of the genetic control of traits associated with a “smart canopy” in sorghum.
Leaf angle has been an important trait manipulated to enhance yield for corn and some other crops. Plants with leaves upright at the top and more horizontal toward the bottom are idealized as having a “smart canopy” leaf arrangement, predicted to intercept more light, boost photosynthesis and increase yields.
This approach has not been a focus for improving sorghum, an important cereal crop worldwide for grain and forage production with potential as a bioenergy feedstock. The new research from Iowa State, studying sorghum leaf angle patterns and their underlying genetics and physiology, sheds light on opportunities to increase sorghum production. The findings were published recently in the peer-reviewed journal, Plant Physiology.
Seed banks across the globe store and preserve the genetic diversity of millions of varieties of crops. This massive collection of genetic material ensures crop breeders access to a wealth of genetics with which to breed crops that yield better or resist stress and disease.
But, with a world of corn genetics at their disposal, how do plant breeders know which varieties are worth studying and which ones aren’t? For most of history, that required growing the varieties and studying their performance in the real world. But innovative data analytics and genomics could help plant breeders predict the performance of new varieties without having to go to the effort of growing them.
Overexpression of soybean gene might lead to resistance from SDS and more
No matter if it is 50 acres or 50,000, crop producers must hone their management practices to maximize yield while minimizing costs. Any number of different pathogens or pests can derail a good season. Soybean farmers in Iowa know how devastating they can be, with some causing millions in losses each year.
A recently published study led by Iowa State University scientists applied a fresh perspective to vast amounts of data on rice plants to find better ways to predict plant performance and new insights about how plants adapt to different environments.
The study, published in the academic journal Genome Research, unearthed patterns in datasets collected on rice plants across Asia, said Jianming Yu, professor of agronomy and Pioneer Distinguished Chair in Maize Breeding. Those patterns allowed the researchers to develop a matrix to help them predict the traits of rice plants depending on their genetics and the environment in which they’re grown. The research could improve the ability of farmers to predict how crop varieties will perform in various environments, giving growers a better sense of stability and minimizing risk, Yu said.